Background: The splitter blade is an improved structure effective in traditional pumps. However, applying splitter blades to blood pumps is a complex optimization problem with multiple parameters and objectives, because structural parameters, blood circulation dynamics, and blood damage need to be considered simultaneously. This study aims to obtain the performance impact of the splitter blade and make it well used in blood pumps through CFD and neural networks.Results: This study combines CFD and neural networks. And hydraulic experiments and PIV technology were used. In the optimization study, the number of blades, axial length, and circumferential offset are optimization parameters, and hydraulic performance and hemolytic prediction index are optimization targets. The study analyzes the influence of each parameter on performance and completes the optimization of the parameters. In the results, the optimal parameters of the number of blades, axial length ratio, and circumferential offset are 2, 6 °, and 0.41, respectively. Under optimized parameters, hydraulic performance can be significantly improved. And the results of hemolysis prediction and micro PIV experiments reflect that there is no increase in the risk of hemolytic damage.Conclusion: This study provides a method and ideas for improving the structure of the blood pump. The established optimization method can be effectively applied to the design and research of blood pumps with complex, high precision, and multiple parameters and targets.